• Communications for Statistical Applications and Methods
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• v.21 no.4
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• pp.275-284
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• 2014

Matched pairs are twice continuously measured data with the same categories. They can be represented as the square contingency tables. We can also consider symmetry and marginal homogeneity. Moreover, we can infer the matched pairs models; the symmetry model, the quasi-symmetry model, and the ordinal quasi-symmetry model. These inferences are involved in assumptions for special distributions. In this study, we visualize matched pairs models using modified correspondence analysis. Modified correspondence analysis can be used when square contingency tables are given; consequently, it is involved in the square and asymmetric correspondence matrix. This technique does not need assumptions for special distributions and is more helpful than the correspondence analysis to visualize matched pairs models.

• Communications for Statistical Applications and Methods
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• v.24 no.6
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• pp.641-649
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• 2017

Multivariate confidence regions were defined using a chi-square distribution function under a normal assumption and were represented with ellipse and ellipsoid types of bivariate and trivariate normal distribution functions. In this work, an alternative confidence region using the multivariate quantile vectors is proposed to define the normal distribution as well as any other distributions. These lower and upper bounds could be obtained using quantile vectors, and then the appropriate region between two bounds is referred to as the quantile confidence region. It notes that the upper and lower bounds of the bivariate and trivariate quantile confidence regions are represented as a curve and surface shapes, respectively. The quantile confidence region is obtained for various types of distribution functions that are both symmetric and asymmetric distribution functions. Then, its coverage rate is also calculated and compared. Therefore, we conclude that the quantile confidence region will be useful for the analysis of multivariate data, since it is found to have better coverage rates, even for asymmetric distributions.

• Proceedings of the Korean Society For Composite Materials Conference
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• 2005.04a
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• pp.195-198
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• 2005

The role of elastic/plastic mismatch on the contact crack initiation is investigated for designing desirable surface-coated asymmetric layered composites. Various layered composites such as $Si_3N_4$ ceramics on $Si_3N_4+BN$ composite, soda-lime glass on various substrates with different elastic modulus for the analysis. Spherical indentation is conducted for producing contact cracks from the surface or interface between the coating and the substrate layer. A finite element analysis of the stress fields in the loaded layer composites enables a direct correlation between the damage patterns and the stress distributions. Implications of these conclusions concerning the design of asymmetric layered composites indicate that the elastic modulus mismatch is one of the important parameter for designing layered composite to prevent the initiation of contact cracks.

• 한국가시화정보학회:학술대회논문집
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• 2006.12a
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• pp.21-24
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• 2006

Transient and asymmetric density distributions have been investigated by a digital speckle tomography with a novel integration method. Multiple CCD images captured movements of speckles in three angles of view simultaneously because the flows were asymmetric and unsteady. The speckle movements which have been formed by a ground glass between no flow and downward butane flow from an elliptical nozzle have been calculated by a cross-correlation tracking method so that those distances can be transferred to deflection angles of laser rays for density gradients. A novel integration method has been developed to obtain projection data from the deflection angles for the speckle tomography. The unsteady density fields have been reconstructed from the accurate projection values by the digital speckle tomography method using the developed integration method.

• Communications for Statistical Applications and Methods
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• v.28 no.6
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• pp.627-641
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• 2021

An asymmetric least squares estimation method has been employed to estimate linear models for percentile regression. An asymmetric maximum likelihood estimation (AMLE) has been developed for the estimation of Poisson percentile linear models. In this study, we propose generalized nonlinear percentile regression using the AMLE, and the use of the parametric bootstrap method to obtain confidence intervals for the estimates of parameters of interest and smoothing functions of estimates. We consider three conditional distributions of response variables given covariates such as normal, exponential, and Poisson for three mean functions with one linear and two nonlinear models in the simulation studies. The proposed method provides reasonable estimates and confidence interval estimates of parameters, and comparable Monte Carlo asymptotic performance along with the sample size and quantiles. We illustrate applications of the proposed method using real-life data from chemical and radiation epidemiological studies.

• Nuclear Engineering and Technology
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• v.53 no.2
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• pp.357-367
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• 2021

In general, common cause failures (CCFs) have been modeled with the assumption that components within the same group are symmetric. This assumption reduces the number of parameters required for the CCF probability estimation and allows us to use a parametric model, such as the alpha factor model. Although there are various asymmetric conditions in nuclear power plants (NPPs) to be addressed, the traditional CCF models are limited to symmetric conditions. Therefore, this paper proposes the copulabased CCF model to deal with asymmetric as well as symmetric CCFs. Once a joint distribution between the components is constructed using copulas, the proposed model is able to provide the probability of common cause basic events (CCBEs) by formulating a system of equations without symmetry assumptions. In addition, Bayesian inferences for the parameters of the marginal and copula distributions are introduced and Markov Chain Monte Carlo (MCMC) algorithms are employed to sample from the posterior distribution. Three example cases using simulated data, including asymmetry conditions in total failure probabilities and/or dependencies, are illustrated. Consequently, the copula-based CCF model provides appropriate estimates of CCFs for asymmetric conditions. This paper also discusses the limitations and notes on the proposed method.

• Nuclear Engineering and Technology
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• v.55 no.5
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• pp.1651-1664
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• 2023

It is very difficult to capture the multi-dimensional phenomena such as asymmetric flow and temperature distributions with the one-dimensional (1D) model, obviously, due to its inherent limitation. In order to overcome such a limitation of the 1D representation, many state-of-the-art system codes have equipped a three-dimensional (3D) component for multi-dimensional analysis capability. In this study, a standard multi-dimensional analysis model of APR1400 (Advanced Power Reactor 1400) has been developed using TRACE (TRAC/RELAP Advanced Computational Engine). The entire reactor pressure vessel (RPV) of APR1400 has been modeled using a single 3D component. The fuels in the reactor core have been described with detailed and coarse representations, respectively, to figure out the impact of the fuel description. Using both 3D RPV models, a comparative analysis has been performed postulating a double-ended guillotine break at a cold leg. Based on the results of comparative analysis, it is revealed that both models show no significant difference in general plant behavior and the model with coarse fuel model could be used for faster transient analysis without reactor kinetics coupling. The analysis indicates that the asymmetric temperature and flow distributions are captured during the transient, and such nonuniform distributions contribute to asymmetric quenching behaviors during blowdown and reflood phases. Such asymmetries are directly connected to the figure of merits in the LBLOCA analysis. Therefore, it is recommended to employ a multi-dimensional RPV model with a detailed fuel description for a realistic safety analysis with the consideration of the spatial configuration of the reactor core.

• Communications for Statistical Applications and Methods
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• v.9 no.1
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• pp.101-113
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• 2002

In this paper we introduce a new score generating (unction for the rank regression in the linear regression model. The score function compares the $\gamma$'th and s\`th power of the tail probabilities of the underlying probability distribution. We show that the rank estimate asymptotically converges to a multivariate normal. further we derive the asymptotic Pitman relative efficiencies and the most efficient values of $\gamma$ and s under the symmetric distribution such as uniform, normal, cauchy and double exponential distributions and the asymmetric distribution such as exponential and lognormal distributions respectively.

• Journal of the Korean Data and Information Science Society
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• v.16 no.1
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• pp.33-40
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• 2005

The estimating function method was proposed by Godambe(1985) for parameter estimation under unknown distributions for errors in the models. Threshold Autoregressive Heteroscedastic (Threshold-ARCH) models have been developed by Zakoian(1994) and Li and Li(1996) for explaining the asymmetric properties in the financial time series data. In this paper, we apply the estimating function method to the Threshold-ARCH model and show that the proposed estimators perform better than the MLE under the heavy-tailed distributions.

• Journal of the Korean Society of Visualization
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• v.16 no.2
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• pp.31-37
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• 2018

Ischemic mitral regurgitation (IMR) is the primary mitral valve (MV) pathology in the aftermath of myocardial infarction as a consequence of regional left ventricular (LV) remodeling. We investigated the effect of asymmetric papillary muscle (PM) displacement and annular dilation on IMR development. Virtual MV modeling was performed to create a normal human MV. Asymmetric PM displacement, asymmetric annular dilation, and the combination of these two pathologic characteristics were modeled. Dynamic finite element evaluation of MV function was performed across the complete cardiac cycle for the normal and three different IMR MV models. While the normal MV demonstrated complete leaflet coaptation, each pathologic MV model clearly revealed deteriorated leaflet coaptation and abnormal stress distributions. The pathologic MV model having both asymmetric PM displacement and annular dilation showed the worst leaflet malcoaptation. Simulation-based biomechanical evaluation of post-ischemic LV remodeling provides an excellent tool to better understand the pathophysiologic mechanism of IMR development.